Berichtzusammenfassung

The COCA computer code for the design, operation and optimization of lignite burners and boilers

The COCA code is capable of predicting pulverised coal combustion in a 3-dimensional utility boiler geometry. Additionally, there are also other forms of the code that can be applied on 2-dimensional axisymmetric furnaces. The algorithm is based on a Eulerian description for the gas phase, for which the continuity, momentum, the species concentration (oxygen, carbon dioxide, water, volatiles) and radiation transport equations are solved by means of the SIMPLE algorithm.

The coal particles and their motion are described using the Lagrangian approach. During the motion of the particles there is interaction with the ambient gas, which produces momentum and energy source terms, properly accommodated in the equations of the continuous phase.

The gas phase equations are discretised by applying Cartesian computational grids to the furnace geometry, in conjunction with the porosity methodology near inclined surfaces. The local grid refinement method, which has been lately implemented, saves an important amount of memory and computational time, by dealing with the most important areas of the flow inside the furnace. The gas phase equations are discretised by integration over the cell control volumes. The code uses several higher order accurate difference schemes for the calculation of the transported variables on the cell faces. Schemes such as the BSOU (bonded second order upwind) and VONOS (variable order non oscillatory scheme) are used for the computations. The advantage of higher order discretisation schemes is that they provide accurate solutions in standard computational cells and CPU time.

Additionally, the nitrogen oxide emissions are predicted by means of a post-processor. The nitrogen oxide post-processor takes into account the turbulent fluctuations of the temperature and oxygen field, but it also has the possibility of a deterministic nitrogen oxide emissions calculation. The effect of temperature and oxygen turbulent fluctuations is taken into account by a statistical approach, assuming two statistically independent variables with an associated density-weighted probability density function (pdf).